Data Modeler - Insurance (Contract)

Morgan Mckinley Limited; Hong Kong; On-site; HKD 480,000 - 780,000; Part time

Job summary

Morgan McKinley Limited in Hong Kong is seeking a Data Modeler on a 12-month contract to drive a large-scale digital and data transformation for a multinational insurance group. You will lead modeling across policy, claims, customer, actuarial, and financial processing domains and collaborate with data governance and engineering teams.

Ideal candidates bring 5+ years of data modeling/warehousing experience, strength in relational and dimensional design, and hands-on use of erwin Data Modeler or

Qualifications

• Bachelor's degree in Computer Science, Information Systems, Data Management, or a related technical discipline.
• Minimum of 5 years of hands-on experience in data modeling, data architecture, data warehousing, or data engineering.
• Strong SQL skills and experience with cloud platforms (Azure, AWS, Databricks, Delta Lake) and streaming structures (Kafka, Avro, JSON).

Responsibilities

• Lead data modeling initiatives across enterprise digital applications, translating complex requirements into robust conceptual, logical, and physical data models.
• Develop normalized, dimensional, canonical, and lakehouse data schemas for core insurance domains (policy, customer, claims, actuarial, and financial processing).
• Partner with business analysts and SMEs to establish standardized definitions, data lineage, master data rules, and business glossary alignments.
• Collaborate with data engineering teams to convert models into lakehouse tables, database structures, APIs, and streaming event layers.
• Work with data governance and security teams to implement data quality rules, classifications, retention controls, and auditability metrics.
• Maintain model repositories, version controls, naming conventions, and architectural decision records across the organization.

Skills

Data modeling

Data architecture

Data warehousing

Data engineering

SQL skills

Education

Bachelor's degree in Computer Science, Information Systems, Data Management, or related technical discipline

Tools

erwin Data Modeler

ER/Studio

Job description

Our client is a prominent, multinational insurance group based in Hong Kong that is driving a large-scale digital and data transformation. They operate across multiple regional markets, building advanced cloud data platforms to enhance customer experience, enterprise analytics, and AI capabilities.

They are looking for a Data Modeler on 12 months contract basis for a transformation project.

Key Responsibilities

• Lead data modeling initiatives across the Group's enterprise digital applications, translating complex requirements into robust conceptual, logical, and physical data models.
• Develop normalized, dimensional, canonical, and lakehouse data schemas for core insurance domains including policy, customer, claims, actuarial, and financial processing.
• Partner with business analysts and SMEs to establish standardized definitions, data lineage, master data rules, and business glossary alignments.
• Collaborate closely with data engineering teams to convert approved models into lakehouse tables, database structures, APIs, and streaming event layers.
• Work alongside data governance and security teams to implement data quality rules, classifications, retention controls, and auditability metrics.
• Maintain model repositories, version controls, naming conventions, and architectural decision records across the organization.

Requirements

• Bachelor's degree in Computer Science, Information Systems, Data Management, or a related technical discipline.
• Minimum of 5 years of hands-on experience in data modeling, data architecture, data warehousing, or data engineering.
• Strong expertise in relational modeling, dimensional design, slowly changing dimensions, and modeling platforms such as erwin Data Modeler or ER/Studio.
• Solid background in the insurance industry, with deep knowledge of domains like policy, claims, product, reinsurance, or billing.
• Strong SQL skills for data profiling, with exposure to cloud platforms (Azure, AWS, Databricks, Delta Lake) and streaming structures (Kafka, Avro, JSON).
• Excellent analytical, facilitation, and stakeholder management skills, with the ability to articulate complex data concepts to both technical and non-technical teams.